AI in your CRM, with the boring parts done properly

The question is not whether AI can draft a case response. It’s whether you can explain, three months later, why it said what it said to a customer who complained.

We implement Salesforce AI the way we’d implement anything that touches a customer: define the bounded task, ground it in a source of truth you control, put a guardrail on the output, give it an escalation path to a person, and log everything. Then measure whether it actually reduced handling time, rather than moving effort into review.

Where a use case isn’t ready — open-ended conversation about money, health or eligibility, for instance — we’ll say so and propose the assistive version instead, where a human stays in the loop and the AI drafts rather than decides.

What you get

• Bounded scope first. Triage, summarise, draft, retrieve — tasks where “wrong” is recoverable.
• Grounded in your data. Retrieval from your knowledge base and CRM records, not model recall.
• Guardrails and refusal paths. Defined topics the agent hands off rather than attempts.
• Full audit trail. Every action, source and escalation logged and reportable.
• Measured against a baseline. We record handling time and quality before switching anything on.
• Reversible. A switch-off path that degrades to the previous process, not to chaos.

What we build

Agentforce service agents (case triage, deflection, knowledge answers) · Sales agents (research briefs, meeting prep, next-step drafting) · Einstein/Prompt Builder templates grounded in CRM data · Knowledge base restructuring for retrieval quality · Escalation and hand-off design · Evaluation harness with a labelled test set · Monitoring dashboard for containment, escalation and quality Data foundation: Data Cloud profile unification, consent flags, retention rules, PII handling and redaction.

How we run it

01 Use-case triage — Score candidate tasks on risk, volume, and how measurable “good” is. 02 Baseline — Measure the human process first. Without this, no claim about improvement is credible. 03 Ground — Fix the knowledge and data the agent will draw on. This is usually the longest step. 04 Pilot — One task, one team, human review on every output, labelled evaluation set. 05 Widen — Reduce review as quality holds, expand scope by one boundary at a time. 06 Monitor — Containment rate, escalation reasons, quality sampling, drift review each month.

What you receive

Use-case risk register · Baseline measurement report · Grounding and knowledge remediation plan · Agent configuration in source control · Guardrail and escalation specification · Labelled evaluation set and results · Monitoring dashboard · Responsible-use notes for your team · Rollback procedure

Common questions